The Black Box of Perinatal Ischemic Stroke Pathogenesis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
An improved understanding of perinatal stroke epidemiology, classification, neuroimaging, and outcomes has emerged in recent years. Despite this, little is known regarding the pathophysiological mechanisms responsible for most cases. A multitude of possible associations and putative risk factors have been reported, but most lack definitive empirical evidence supporting primary causation. These include obstetrical and maternal factors, perinatal conditions, infectious diseases, prothrombotic abnormalities, cardiac disorders, medications, and many others. The bulk of evidence is weak, dominated by case reports and retrospective case series. Findings from the small number of case-control and cohort studies that exist are limited by heterogeneous populations and methodologies. The single largest barrier to ultimately understanding and potentially improving outcomes from this common and disabling condition is the lack of comprehensive, fully powered risk factor studies required to definitively describe perinatal stroke pathogenesis. This review summarizes current evidence and suggests future directions for research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it